Mutation Free Energy Calculations using BioExcel Building Blocks (biobb) (jupyter notebook)

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Summary

This tutorial aims to illustrate how to compute a fast-growth mutation free energy calculation, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Staphylococcal nuclease protein (PDB code 1STN), a small, minimal protein, appropriate for a short tutorial.

Workflow engine is a jupyter notebook. Auxiliary libraries used are nb_conda_kernels, os, and plotly. Environment setup can be carried out using the environment.yml in the code repository. The tutorial uses docker for running pmx - a local setup can be used instead, see notes in the tutorial.

Parameters

Inputs

Workflow Input files needed:

  • stateA_traj: Equilibrium trajectory for the WT protein.

  • stateB_traj: Equilibrium trajectory for the Mutated protein.

  • stateA_tpr: WT protein topology (GROMACS tpr format).

  • stateB_tpr: Mutated protein topology (GROMACS tpr format).

Auxiliar force field libraries needed:

  • mutff45 (folder): pmx mutation force field libraries.

Outputs

  • pmx.outputs: Final free energy estimation. Summary of information got applying the different methods.

  • pmx.plots.png: Final free energy plot of the Mutation free energy pipeline.

help Creators and Submitter
Citation
Lowe, D., & Bayarri, G. (2021). Mutation Free Energy Calculations using BioExcel Building Blocks (biobb) (jupyter notebook). WorkflowHub. https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.55.2
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Views: 395   Downloads: 24

Created: 15th Sep 2020 at 12:56

Last updated: 13th May 2021 at 09:15

Last used: 25th Jun 2021 at 01:25

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Version History

Version 2 (latest) Created 7th May 2021 at 14:22 by Douglas Lowe

Updated for GROMACS 2020.4 and BioExcel Building Blocks version 3.5. Taken from Git commit ba3c37d

Version 1 (earliest) Created 15th Sep 2020 at 12:56 by Douglas Lowe

Initial commit. Taken from Git commit 3272c52

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